In the context of NMT, several researchers leverage document-level context for NMT [1]}, [2]}, [3]}, while we opt for sentential context.
In addition, contextual information are used to improve the encoder representations [4]}, [5]}, [6]}. Our approach is complementary to theirs by better exploiting the encoder representations for the subsequent decoder.
Concerning guiding the NMT generation with source-side context, zheng2018modeling split the source content into translated and untranslated parts, while we focus on exploiting global sentence-level context.
